Name
Abstract | ||
|---|---|---|
We propose a method for source separation of convolutive mixture based on nonlinear prediction-error filters. This approach converts the original problem into an instantaneous mixture problem, which can be solved by any of the several existing methods in the literature. We employ fuzzy filters to implement the prediction-error filter, and the ecacy of the proposed method is illustrated by some examples. |
Year | DOI | Venue |
|---|---|---|
2007 | 10.1155/2007/43860 | EURASIP J. Adv. Sig. Proc. |
Keywords | Field | DocType |
nonlinear prediction approach,nonlinear prediction-error filter,instantaneous mixture problem,existing method,prediction-error filter,original problem,convolutive mixture,fuzzy filter,blind separation,source separation | Signal processing,Computer vision,Nonlinear system,Computer science,Fuzzy logic,Algorithm,Speech recognition,Artificial intelligence,Estimation theory,Quantum information,Source separation,Nonlinear prediction | Journal |
Volume | Issue | ISSN |
2007 | 1 | 1687-6180 |
Citations | PageRank | References |
2 | 0.47 | 10 |
Authors | ||
8 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Ricardo Suyama | 1 | 62 | 12.44 |
| Leonardo Tomazeli Duarte | 2 | 86 | 15.42 |
| Rafael Ferrari | 3 | 23 | 3.81 |
| Leandro Elias Paiva Rangel | 4 | 2 | 0.47 |
| Romis de Faissol Attux | 5 | 30 | 4.13 |
| Charles Casimiro Cavalcante | 6 | 45 | 14.78 |
| Fernando José Zuben | 7 | 28 | 4.71 |
| João Marcos Travassos Romano | 8 | 175 | 27.76 |